SYSTEM AND METHOD FOR CREATING A VIRTUAL DATA WAREHOUSE

• US 20020038308A1
• Filed: 05/27/1999
• Published: 03/28/2002
• Est. Priority Date: 05/27/1999
• Status: Abandoned Application

• Current Assignee: Matamatrix Incorporated
• Original Assignee: Matamatrix Incorporated
• Inventors: CAPPI, MICHAEL
• Application Number:
  US09/320,896
• Publication Number:
  US 20020038308A1
• Time in Patent Office: Days
• US Class Current: 707/104.1
• CPC Class Codes: G06F 16/256 in federated or virtual databases

Abstract

A system and method for creating a global data dictionary from a plurality of databases such that users may conduct expansive searches or queries, and retrieve data therefrom, regardless of the database management system from each respective database. The global data dictionary is created by semantically and syntactically integrating data elements from the plurality of databases. The plurality of data elements are stored in a dictionary system, wherein each of the data elements corresponds to at least one data element in the plurality of databases. Relationships are identified between two or more of the data elements in the dictionary system. In order to retrieve data, upon receiving from a user a request for data in the form of a query data element, the system identifies the data elements in the dictionary system that corresponds to the query data element and retrieves the data corresponding to the query data element from the databases.

Claims

1. A method for creating a virtual data warehouse employing a plurality of databases, said method comprising the steps of:

storing in a dictionary system a plurality of data elements, each of said data elements corresponding to at least one data element in said plurality of databases;

identifying relationships between two or more of said data elements in said dictionary system;

2. The method of claim 1, further comprising the step of storing said plurality of data elements in a data element dictionary, said data element dictionary configured to identify each said database that said data elements are found in.

3. The method of claim 1, further comprising the step of storing a plurality of keywords in a master keyword dictionary, said plurality of keywords further comprising a list of every said data element, a group of industry words, and each said keyword having a synonym set.

4. The method of claim 3, wherein, in said step of storing said plurality of keywords in said master keyword dictionary, said synonym set of each said keyword comprises a plurality of words having a relationship with said keyword.

5. The method of claim 4, wherein, in said step of storing said plurality of keywords in said master keyword dictionary, said plurality of words having a relationship with said keyword comprises a plurality of said data elements.

6. The method of claim 5, further comprising the step of maintaining, in said master keyword dictionary, a weight for each relationship between a keyword and each word in said keyword'"'"'s synonym set, said weight corresponding to a measure of similarity between said keyword and each word in said keyword'"'"'s synonym set.

7. The method of claim 6, further comprising the step of storing, in an ambiguity data element dictionary, a plurality of ambiguous data elements, said ambiguous data elements comprising data elements from said databases that have the same name as another data element but a different meaning.

8. The method of claim 6, further comprising the step of employing an application container to retrieve said data via channels.

9. The method of claim 8, wherein said application container employs a model channel, said model channel configured to retrieve data from a particular data source, and a view channel, said view channel configured to instruct the system to present said data in a specified format.

10. The method of claim 9, wherein said application container employs JavaBeans™

.

11. The method according to claim 1, wherein said method further comprises the step of restricting, via a restricted database component, a retrieval of said data.

12. The method according to claim 11, wherein said step of restricting further comprises restricting the retrieval of a specifiable database.

13. The method according to claim 11, wherein said step of restricting further comprises restricting the retrieval of a specifiable data element.

14. The method according to claim 11, wherein said step of restricting further comprises restricting the retrieval of a row of said data.

15. The method according to claim 11, wherein said step of restricting further comprises restricting the retrieval of a range of rows of said data.

17. The system according to claim 16, further comprising retrieval means configured to retrieve data from said databases in response to a user query.

18. The system of claim 16, wherein said dictionary system comprises a data element dictionary configured to store said plurality of data elements and to identify each said database that said data elements are found in.

19. The system of claim 16, wherein said dictionary system further comprises a master keyword dictionary for storing a plurality of keywords, said plurality of keywords comprising a list of every said data element and a group of industry words, each said keyword having a synonym set.

20. The system of claim 19, wherein said synonym set of each said keyword comprises a plurality of words having a relationship with said keyword.

21. The system of claim 20, wherein said plurality of words having a relationship with said keyword comprises a plurality of said data elements.

22. The system of claim 21, wherein said master keyword dictionary maintains a weight for each relationship between a keyword and each word in said keyword'"'"'s synonym set, said weight corresponding to a measure of similarity between said keyword and each word in said keyword'"'"'s synonym set.

23. The system of claim 22, wherein said dictionary system further comprises an ambiguity data element dictionary that is configured to store a plurality of ambiguous data elements, said ambiguous data elements comprising data elements from said databases that have the same name as another data element but a different meaning.

25. The method of claim 24, further comprising the step of storing said plurality of data elements in a data element dictionary, said data element dictionary configured to identify each said database that said data elements are found in.

26. The method of claim 24, further comprising the step of storing a plurality of keywords in a master keyword dictionary, said plurality of keywords further comprising a list of every said data element, a group of industry words, and each said keyword having a synonym set.

27. The method of claim 26, wherein, in said step of storing said plurality of keywords in said master keyword dictionary, said synonym set of each said keyword comprises a plurality of words having a relationship with said keyword.

28. The method of claim 27, wherein, in said step of storing said plurality of keywords in said master keyword dictionary, said plurality of words having a relationship with said keyword comprises a plurality of said data elements.

29. The method of claim 28, further comprising the step of maintaining, in said master keyword dictionary, a weight for each relationship between a keyword and each word in said keyword'"'"'s synonym set, said weight corresponding to a measure of similarity between said keyword and each word in said keyword'"'"'s synonym set.

30. The method of claim 29, further comprising the step of storing, in an ambiguity data element dictionary, a plurality of ambiguous data elements, said ambiguous data elements comprising data elements from said databases that have the same name as another data element but a different meaning.

31. The method of claim 29, further comprising the step of employing an application container to retrieve said data via channels.

32. The method of claim 31, wherein said application container employs a model channel, said model channel configured to retrieve data from a particular data source, and a view channel, said view channel configured to instruct the system to present said data in a specified format.

33. The method of claim 31, wherein said application container employs JavaBeans™

.

35. The system of claim 34, wherein said dictionary system comprises a data element dictionary configured to store said plurality of data elements and to identify each said database that said data elements are found in.

36. The system of claim 34, wherein said dictionary system further comprises a master keyword dictionary for storing a plurality of keywords, each said keyword having a synonym set.

37. The system of claim 36, wherein said synonym set of each said keyword comprises a plurality of words having a relationship with said keyword.

38. The system of claim 37, wherein said plurality of words having a relationship with said keyword comprises a plurality of said data elements.

39. The system of claim 38, wherein said master keyword dictionary maintains a weight for each relationship between a keyword and each word in said keyword'"'"'s synonym set, said weight corresponding to a measure of similarity between said keyword and each word in said keyword'"'"'s synonym set.

40. The system of claim 39, wherein said dictionary system further comprises an ambiguity data element dictionary that is configured to store a plurality of ambiguous data elements, said ambiguous data elements comprising data elements from said databases that have the same name as another data element but a different meaning.

16. A global data dictionary system configured to store a plurality of data elements, each of said data elements corresponding to data elements in one of a plurality of databases, said dictionary system further configured to identify relationships between two or more of said data elements.

24. A method for retrieving data from a plurality of databases, said method comprising the steps of:

storing in a dictionary system a plurality of data elements, each of said data elements corresponding to at least one data element in said plurality of databases;

identifying relationships between two or more of said data elements in said dictionary system;

receiving from a user a request for data in the form of a query data element;

identifying at least one of said data elements in said dictionary system that corresponds to said query data element; and

retrieving corresponding data from each of said identified data elements of said databases corresponding to said query data element.

34. A system for facilitating the retrieval of data from a plurality of databases, comprising:

a dictionary system configured to store a plurality of data elements, each of said data elements corresponding to data elements in one of said plurality of databases, said dictionary system further configured to identify relationships between two or more of said data elements; and

retrieval means configured to retrieve data from said databases in response to a user query.